Model reduction is a crucial step in designing controllers for large-scale systems.
When controlling large-scale networks systems, it is difficult to put the system on a microcomputer's memory, and highly accurate feedback control is difficult due to delays caused by insufficient computing power from the viewpoint of the amount of time and required space complexity. Thus, the model reduction for large-scale systems is of importance and some methods have been proposed.
Speaking of general linear systems, model reduction methods have been proposed for years such as the balanced truncation (BT) method proposed in [1]} and the application of the iterative rational Krylov algorithm (IRKA) proposed in [2]}, [3]}, [4]}, [5]}, [6]}.
